R/CellCycle.R

In secure: Sequential Co-Sparse Factor Regression

#' Cell cycle data
#' 
#' A list of two matrices used in Lee (2002).
#' 
#' Matrix X, the chromatin immunoprecipitation (ChIP) data contain complete binding 
#' information of a subset of 1790 genes for a total of 113 transcription 
#' factors.
#' 
#' Matrix Y, the Eukariotic cell cycle data were generated using alpha factor arrest method,
#' consisting of RNA levels measured every 7 minutes for 119 minutes with a total 
#' of 18 time points covering two cell cycle of 1790 genes.
#'
#' @docType data
#'
#' @usage data(CellCycle)
#'
#' @format A list with two components: 
#' \describe{
#'   \item{X}{Chromatin immunoprecipitation data, a matrix of 1790 rows and 113 columns.}
#'   \item{Y}{Eukariotic cell cycle data, a matrix of 1790 rows and 18 columns.}
#' }
#'
#' @keywords datasets

#' @examples
#' # data(CellCycle)
#' # X <- CellCycle$X;Y <- CellCycle$Y
#' # n <- nrow(Y); p <- ncol(X); q <-  ncol(Y)
#' # control <- secure.control(spU=160/p,spV=1)
#' # fit.cycle <- secure.path(Y, X, nrank = 10, nlambda = 100,
#' #                   control = control)
#' @references Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., 
#' Hannett, N. M., Harbison, C. T., Thompson, C. M., Simon, I. et al. (2002) \emph{Transcriptional
#' regulatory networks in saccharomyces cerevisiae. Science, 298, 799-804}.
"CellCycle"